Test cost sensitivity using PRCC

Test cost sensitivity using PRCC

test_prcc(df = NULL, params = NULL, target_time = NULL)

Arguments

df	A dataframe of cost effectiveness data. As produced by combine_data.
params	A dataframe of parameters used to generate model simulations. See example_parameters for an example dataset
target_time	Numeric, the time at which to estimate the model sensitivity. If not specified then this will default to the last fitted point that the model has produced output for.

Value

A data frame containing the names of the parameters in the model, the correlation with the outcome and the p value of this correlation

Examples

## Code
test_prcc
#> function (df = NULL, params = NULL, target_time = NULL) 
#> {
#>     time <- NULL
#>     value <- NULL
#>     Parameter <- NULL
#>     p.value <- NULL
#>     df <- df %>% dplyr::filter(time == target_time) %>% select_if(~var(.) > 
#>         0)
#>     sample <- params %>% bind_cols(df %>% select(value) %>% setNames("Observation"))
#>     prcc <- epi.prcc(sample) %>% mutate(Parameter = colnames(params)) %>% 
#>         select(Parameter, gamma, p.value) %>% arrange(desc(abs(gamma)))
#>     return(prcc)
#> }
#> <bytecode: 0xa03c0b8>
#> <environment: namespace:ceplotr>